Driving towards fully autonomous mobility

Time of India

26-06-2025

The
future of mobility
is fueled by four major disruptive trends viz
autonomous mobility
, connectivity, shared and electric mobility. Autonomous mobility is a monumental engineering challenge that promises to revolutionize the future of mobility. In the future, a relaxed car journey will involve the vehicle autonomously driving and navigating the majority of the trip. The driver will have the freedom to unwind but remains prepared to assume control if needed. In India, the autonomous vehicle market is projected to grow at a CAGR of 20.8per cent from 2022 to 2032. However, achieving this level of autonomy requires overcoming complex safety, comfort, and low-speed maneuvering challenges.
The global autonomous vehicle market size is projected to grow from $1,921.1 billion in 2023 to $13,632.4 billion by 2030, at a CAGR of 32.3per cent during the forecast period. Asia Pacific dominated the autonomous vehicle industry with a market size of 50.44per cent in 2022.
An Overview of the Levels of Autonomy
The Society of Automotive Engineers (SAE) defines five levels of vehicle automation. Level 0 is No Automation where the driver is in complete control of the vehicle at all times. Level 1 is Driver Assistance that features cruise control and lane-keeping assist that supports the driver. Level 2 is
Partial Automation
where advanced systems control both steering and acceleration/deceleration, but the driver has to be engaged. In Level 3's Conditional Automation, vehicles handle all facets of driving, but the driver must be ready to take over anytime. Level 4's High Automation has vehicles performing all driving tasks without driver intervention but only in specific geographic location.
Level 5 is what Full Automation is and here vehicles operate independently under all conditions with zero human input and it is a huge engineering challenge. Level 5 automation aims an environment where the vehicle operates independently without any human intervention – this is a no eyes, no hands, and no brain required from the driver scenario. However, achieving this level of autonomy necessitates addressing multiple safety, comfort, and low-speed maneuvering challenges. The current focus however, is on systematically mastering these complexities from L2 to L4, and eventually paving the way for the L5 autonomy.
The Pathway to Full Autonomy
The Foundation: Safety
While shifting through the levels of automation and reduction of human interaction from driving, safety becomes supreme. Level 5 vehicles are fully autonomous and have to therefore feature redundant systems to ensure that their operation is fail-safe. With a redundant system in place, if the primary system fails, a backup system takes over to guide the vehicle to safety. This model has been long established in aeronautical engineering and is also crucial for fully autonomous driving.
Presently, the main focus is on providing safety which comprises of integrating ADAS technology, aligning with various NCAP (New Car Assessment Program) standards. These include some of the key functionalities like vulnerable road user detection (pedestrians, cyclists, animals) and obstacle identification (lost cargo). The systems must have the ability to emulate human perception and decision-making by leveraging AI and ML to recognize and react to many complex and unpredictable scenarios.
The challenge lies in the diverse conditions these autonomous systems must handle, including the existing infrastructure. Recreating the human eye's perception and teaching it to the machine is a significant challenge, as there is no exact shape or size to define objects like lost cargo. Efforts are underway to define what constitutes lost cargo, but the ability to identify such unpredictable scenarios is crucial.
As a result, AI and machine learning are becoming integral in enabling autonomous vehicles to perceive and interpret their environment, akin to human drivers. Establishing clear boundaries for AI behavior and alignment with safety/legal standards is crucial as AI can hallucinate and make up responses based on its understanding. The need for AI/ML in decision-making or enabling vehicle functions is a subject of ongoing discussions.
There is also a deliberation on the applicability of Level 5 automation across all vehicle segments. Some argue it can be used primarily for commercial vehicles like trucks, especially in developed countries, while its practicality for passenger vehicles is questionable.
Since 2018,
Continental
has been progressively integrating cabin sensing, V2X communication deployment, and advanced autonomous driving test suites. These initiatives address scenarios such as vehicle interactions with moving and stationary objects, as well as crossing pedestrians and cyclists. Important use cases include managing longitudinal movements, executing turning maneuvers, and handling oncoming traffic, all of which are crucial for ensuring safety.
Driving Experience Enhancement: Comfort
Comfort enhancements are key while moving up the levels of automation and at L2, features like adaptive cruise control and lane-keeping assistance reduce driver load through long drives. L3 allows drivers to delegate control and give a relaxing and stress-free driving experience. L4 takes it a step further and enables the vehicle to handle all driving tasks within specific geographical locations. This includes advanced cruising functions including traffic jam assistance and highway autopilot that allow drivers to disengage from driving tasks and enhances daily commute significantly.
Continental focuses on developing cruising functions like adaptive cruise control, lane departure prevention, traffic continuation indication, and active lane change assist. These systems support drivers on longer journeys and allows them to relax and enjoy their driving experience.
Low-Speed Maneuvering: Mastering Parking and More
Low-speed maneuvering, mainly parking, is also an important aspect of autonomous driving. At L2, automated parking systems can assist drivers in parking maneuvers. L3 and L4 vehicles will further refine these capabilities and allow vehicles to independently navigate complex parking scenarios. This necessitates sophisticated sensor arrays and processing power so that the vehicle's surrounding can be accurately detected and interpreted. The challenge here is to ensure that these systems can operate reliably in varied environments – be it a crowded urban street or a spacious parking lot.
The India Story of Autonomy
India comes with its own unique set of challenges for autonomous driving due to its different traffic conditions and complex infrastructure. Unlike in mature markets where lane discipline is strictly followed, drivers in India have to navigate through chaotic traffic. This makes it difficult to decide whether to focus on the vehicle that is directly ahead or those in adjacent. This necessitates observing numerous vehicles simultaneously in order for autonomous mobility to be successful.
Object tracking being one of the major challenges to maintain safety and it can further get complicated by hardware limitations of small sensors, like cameras and radars. These sensors must process vast amounts of data, but their processing power is limited. This requires writing efficient codes that the hardware can handle, and they must be particularly tailored for India's conditions, developed especially for the India market.
Indian OEMs recognize the complexities and are willing to accept solutions with certain limitations, such as focusing on forward warnings and mitigating why certain scenarios cannot be handled. The variability in road conditions, from expressways to urban roads, requires customization. For example, a safe cruising distance of five meters in Germany might need to be reduced to three meters in India. Challenges like thick fog in Delhi or navigating Ghats with multiple road users are some unique use cases that must be addressed uniquely in India.
Though India's scenario is complex, it is solvable. AI and ML can be leveraged as enablers. There are challenges like pothole and hump detection that are difficult for cameras and radars to accurately identify – these also present opportunities for innovation. And these solutions, once developed, can be highly marketable.
Likewise, addressing the variability in lane markers and other road features can position India as a hub for pioneering solutions that solve global problems. Today we have several start-ups too in India in this space, who are bringing creative and innovative solutions. Greater collaboration with industry bodies and government will spur innovation and also increase intellectual property creation in India.
Currently, the focus is on deploying Level 2 ADAS to enhance safety and support drivers in complex scenarios. It might even go up to Level 2 plus. The variability in road conditions and traffic behavior requires highly adaptive and robust systems. Addressing the challenges of non-standard vehicles, unpredictable obstacles including animal crossing, and dense traffic provides a valuable framework for enhancing autonomous systems worldwide. Continental is looking forward to the dynamic change that the India market brings in autonomy.
Clear government policies which support the development and testing of autonomous vehicles will improve the situation, as also increased focus on infrastructure development.
The Road Ahead
The path to Level 5 autonomy is an incremental journey through mastering safety, comfort, and low-speed maneuvering at each level of automation. While fully autonomous vehicles may seem distant, the progress made at each step brings the industry closer to this reality. While advancing through Levels 2 to 4, Continental is laying a robust foundation for the future, ensuring that autonomous mobility is safe, comfortable, and efficient.
By addressing the unique challenges posed by the Indian market, Continental not only caters to local needs but also pioneer solutions that can be adapted globally. The journey is complex, but each milestone achieved brings us closer to the vision of fully autonomous vehicles, reshaping the future of mobility.